Adaptive control of variable-speed wind turbines for power capture optimisation

Abstract

Rotor speed control of wind turbines is a key factor in achieving the maximum power of wind. It is known that a high-performance controller can significantly increase the amount of energy that can be captured from this source. The main problem regarding this issue is the lack of information about the correct dynamic model of the system. This uncertainty of the model is generally associated with unknown parameters (structured uncertainty) and/or external disturbances (unstructured uncertainty). Some adaptive and robust control approaches are developed in the literature in order to deal respectively with structured and unstructured uncertainties. In this paper, to compensate for both types of uncertainty, a robust controller, which includes an adaptive feedforward term, is proposed to track the optimal speed. In addition to considering the uncertainties, another advantage of the presented approach is that, using a smooth control effort, it provides global asymptotic tracking. A complete stability proof of the system is presented, and simulation results illustrate the effectiveness of the controller.

Dynamic sliding mode control of pitch blade wind turbine using sliding mode observer

“…The WTFS cannot capture the maximum power of the wind in various wind speeds (Poultangari et al, 2012) and hence, WTVS is developed in recent years (Oh et al, 2015). The strategy to obtain the maximum power of the wind by WTVS, is based on dividing the operation performance using the rated speed of the wind (Jabbari Asl and Yoon, 2016). Below this rated wind speed, the torque of generator is controlled for the maximum power point tracking (MPPT) (Ardjal et al, 2018), and above this rated wind speed, the pitch angle of the blades (PABLE) is used as the input control (Asgharniaa et al, 2018).…”

Adaptive Robust Fault-Tolerant Control Design for Wind Turbines Subject to Pitch Actuator Faults

“…Whereas, in the high wind speed region, wind turbines (WTs) are operated to maintain the generated power at its nominal value by controlling the pitch angle and the generator torque. Designs such as proportional integral derivative (PID) control [3], neural network based-PI control [4], optimal control [5], linear parameter varying (LPV) control [6], gain scheduling [7], robust control [8], adaptive control [9] and fuzzy logic control [10] have traditionally been considered to control wind turbines. However, these solutions fail to operate satisfactorily and exhibit limited control action in the presence of faults.…”

Trade‐off between power extraction maximisation and fatigue reduction in wind farms via second‐order sliding mode control and min–max optimisation

“…The control strategy which is called maximum power point tracking (MPPT) leads to maximise captured power when wind speed is below its rated value. In literature, different control algorithms are proposed to maximise the power and to track the variable angular velocity, starting from proportional–integral–derivative output feedback control [10, 11] to adaptive control [12, 13]. However, due to the aerodynamic interaction, the MPPT strategy of each turbine does not lead to maximal total power capture across the entire wind farm.…”